How to perform RT-qPCR accurately in plant species? A case study on flower colour gene expression in an azalea (Rhododendron simsii hybrids) mapping population

BMC Molecular Biology

Jan De Riek²  Erik Van Bockstaele¹  Laurence Desmet²  Ellen De Keyser² 

[1] Department for Plant Production, Ghent University, Coupure links 653, 9000, Ghent, Belgium;Institute for Agricultural and Fisheries Research (ILVO)-Plant Sciences Unit, Caritasstraat 21, 9090, Melle, Belgium

关键词: Pink;    Gene expression;    Reference genes;    Standard curves;    noRT;    RNA quality;    Flower colour;    RT-qPCR;   

Others  :  1090958
DOI  :  10.1186/1471-2199-14-13

 received in 2012-11-26, accepted in 2013-06-12,  发布年份 2013

【 摘 要 】

Background

Flower colour variation is one of the most crucial selection criteria in the breeding of a flowering pot plant, as is also the case for azalea (Rhododendron simsii hybrids). Flavonoid biosynthesis was studied intensively in several species. In azalea, flower colour can be described by means of a 3-gene model. However, this model does not clarify pink-coloration. The last decade gene expression studies have been implemented widely for studying flower colour. However, the methods used were often only semi-quantitative or quantification was not done according to the MIQE-guidelines. We aimed to develop an accurate protocol for RT-qPCR and to validate the protocol to study flower colour in an azalea mapping population.

Results

An accurate RT-qPCR protocol had to be established. RNA quality was evaluated in a combined approach by means of different techniques e.g. SPUD-assay and Experion-analysis. We demonstrated the importance of testing noRT-samples for all genes under study to detect contaminating DNA. In spite of the limited sequence information available, we prepared a set of 11 reference genes which was validated in flower petals; a combination of three reference genes was most optimal. Finally we also used plasmids for the construction of standard curves. This allowed us to calculate gene-specific PCR efficiencies for every gene to assure an accurate quantification. The validity of the protocol was demonstrated by means of the study of six genes of the flavonoid biosynthesis pathway. No correlations were found between flower colour and the individual expression profiles. However, the combination of early pathway genes (CHS, F3H, F3'H and FLS) is clearly related to co-pigmentation with flavonols. The late pathway genes DFR and ANS are to a minor extent involved in differentiating between coloured and white flowers. Concerning pink coloration, we could demonstrate that the lower intensity in this type of flowers is correlated to the expression of F3'H.

Conclusions

Currently in plant research, validated and qualitative RT-qPCR protocols are still rare. The protocol in this study can be implemented on all plant species to assure accurate quantification of gene expression. We have been able to correlate flower colour to the combined regulation of structural genes, both in the early and late branch of the pathway. This allowed us to differentiate between flower colours in a broader genetic background as was done so far in flower colour studies. These data will now be used for eQTL mapping to comprehend even more the regulation of this pathway.

【 授权许可】

   
2013 De Keyser et al.; licensee BioMed Central Ltd.

【 图 表 】

Figure 1.

Figure 2.

Figure 3.

Figure 4.

【 参考文献 】

• [1]De Loose R: Flavonoid glycosides in the petals of some Rhododendron species and hybrids. Phytochem 1968, 9:875-879.
• [2]De Loose R: The flower pigments of the Belgian hybrids of Rhododendron simsii and other species and varieties from Rhododendron subseries obtusum. Phytochem 1969, 88:253-259.
• [3]Gerats AGM, Martin C: Flavonoid synthesis in Petunia hybrida: genetics and molecular biology of flower colour. In Recent advances in phytochemistry. Edited by Stafford HA, Ibrahim RK. New York: Plenum Press; 1992:165-200.
• [4]Holton TA, Cornish EC: Genetics and biochemistry of anthocyanin biosynthesis. Plant Cell 1995, 7:1071-1083.
• [5]Mol J, Grotewold R, Koes RE: How genes paint flowers and seeds. Trends Plant Sci 1998, 3:212-217.
• [6]Winkel-Shirley B: Biosynthesis of flavonoids and effects of stress. Curr Opin Plant Biol 2002, 5:218-223.
• [7]Schwinn K, Venail J, Shang Y, Mackay S, Alm V, Butelli E, Oyama R, Bailey P, Davies K, Martin C: A small family of MYB-regulatory genes controls floral pigmentation intensity and patterning in the genus Antirrhinum. Plant Cell 2006, 18:831-851.
• [8]De Cooman L, Everaert ESW, Faché P, Vande Casteele K, Van Sumere CF: Flavonoid biosynthesis in petals of Rhododendron simsii. Phytochem 1993, 33:1419-1426.
• [9]De Schepper S, Debergh P, Van Bockstaele E, De Loose M, Gerats A, Depicker A: Genetic and epigenetic aspects of somaclonal variation: flower colour bud sports in azalea, a case study. South African J Bot 2003, 69:117-128.
• [10]Heursel J, Horn W: A hypothesis on the inheritance of flower colours and flavonoids in Rhododendron simsii Planch. Zeitschrift für Pflanzenzüchtung 1977, 79:238-249.
• [11]Sasaki N, Nishizaki Y, Uchida Y, Wakamatsu E, Umemoto N, Momose M, Okamura M, Yoshida H, Yamaguchi M, Nakayama M, Ozeki Y, Itoh Y: Identification of the glutathione S-transferase gene responsible for flower color intensity in carnations. Plant Biotechnol 2012, 29:223-227.
• [12]De Keyser E, Lootens P, Van Bockstaele E, De Riek J: Image analysis for QTL mapping of flower colour and leaf characteristics in pot azalea (Rhododendron simsii hybrids). Euphytica 2013, 189:445-460.
• [13]Nakamura N, Fukuchi-Mizutani M, Fukui Y, Ishiguro K, Suzuki K, Suzuki H, Okazaki K, Shibata D, Tanaka Y: Generation of pink flower varieties from blue Torenia hybrida by redirecting the flavonoid biosynthetic pathway from delphinidin to pelargonidin. Plant Biotechnol 2010, 27:375-383.
• [14]Boase MR, Lewis DH, Davies KM, Marshall GB, Patel D, Schwinn KE, Deroles SC: Isolation and antisense suppression of flavonoid 3′,5′-hydroxylase modifies flower pigments and colour in cyclamen. BMC Plant Biol 2010, 10:107. BioMed Central Full Text
• [15]Nishihara M, Nakatsuka T: Genetic engineering of flavonoid pigments to modify flower color in floricultural plants. Biotechnol Lett 2011, 33:433-441.
• [16]Chen W-H, Hsu C-Y, Cheng H-Y, Chang H, Chen H-H, Ger M-J: Downregulation of putative UDP-glucose: flavonoid 3-O-glucosyltransferase gene alters flower coloring in Phalaenopsis. Plant Cell Rep 2011, 30:1007-1017.
• [17]Kamiishi Y, Otani M, Takagi H, Han D-S, Mori S, Tatsuzawa F, Okuhara H, Kobayashi H, Nakano M: Flower color alteration in the liliaceous ornamental Tricyrtis sp. By RNA interference-mediated suppression of the chalcone synthase gene. Mol Breeding 2012, 30:671-680.
• [18]Nakatsuka T, Mishiba K, Kubota A, Abe Y, Yamamura S, Nakamura N, Tanaka Y, Nishihara M: Genetic engineering of novel flower colour by suppression of anthocyanin modification genes in gentian. J Plant Physiol 2010, 167:231-237.
• [19]Akita Y, Kitamura S, Hase Y, Narumi I, Ishizaka H, Kondo E, Kameari N, Nakayama M, Tanikawa N, Morita Y, Tanaka A: Isolation and characterization of the fragrant cyclamen O-methyltransferase involved in flower coloration. Planta 2011, 234:1127-1136.
• [20]Yamamizo C, Noda N, Ohmiya A: Anthocyanin and carotenoid pigmentation in flowers of section Mina, subgenus Quamoclit, genus Ipomoea. Euphytica 2012, 184:429-440.
• [21]Sui X, Gao X, Ao M, Wang Q, Yang D, Wang M, Fu Y, Wang L: cDNA cloning and characterization of UDP-glucose: anthocyanidin 3-O-glucosyltransferase in Freesia hybrida. Plant Cell Rep 2011, 30:1209-1218.
• [22]Mizuta D, Nakatsuka A, Miyajima I, Ban T, Kobayashi N: Pigment composition patterns and expression analysis of flavonoid biosynthesis genes in the petals of evergreen azalea ‘Oomurasaki’ and its red flower sport. Plant Breeding 2010, 129:558-562.
• [23]De Schepper S, Debergh P, Van Bockstaele E, De Loose M: Molecular characterisation of flower colour genes in azalea sports (Rhododendron simsii hybrids). Acta Hort 2001, 552:143-150.
• [24]Liu X-J, Chuang Y-N, Chiou C-Y, Chin D-C, Shen F-Q, Yeh K-W: Methylation effect on chalcone synthase gene expression determines anthocyanin pigmentation in floral tissues of two Oncidium orchid cultivars. Planta 2012, 236:401-409.
• [25]Livak KJ, Schmittgen TD: Analysis of relative gene expression data using real-time quantitative PCR and the 2(−Delta Delta C(T)) Method. Methods 2001, 25:402-408.
• [26]Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, Mueller R, Nolan T, Pfaffl MW, Shipley GL, Vandesompele J, Wittwer CT: The MIQE guidelines: Minimum Information for publication of Quantitative real-time PCR Experiments. Clin Chemistry 2009, 55:611-622.
• [27]Guttierrez L, Mauriat M, Guénin S, Pelloux J, Lefebvre J, Louvet R, Rusterrucci C, Moritz T, Guerineau F, Bellini C, Van Wuytswinkel O: The lack of a systematic validation of reference genes: a serious pitfall undervalued in reverse transcription – polymerase chain reaction (RT-PCR) analysis in plants. Plant Biotechnol J 2008, 6:609-618.
• [28]Guttierrez L, Mauriat M, Pelloux J, Bellini C, Van Wuytswinkel O: Towards a systematic validation of references in real-time RT-PCR. Plant Cell 2008, 20:1734-1735.
• [29]Guénin S, Mauriat M, Pelloux J, Van Wuytswinkel O, Bellini C, Guttierrez L: Normalization of qRT-PCR data: the necessity of adopting a systematic, experimental conditions-specific, validation of references. J Exp Bot 2009, 60:487-493.
• [30]Vandesompele J, De Preter K, Pattyn F, Poppe B, Van Roy N, De Paepe A, Speleman F: Accurate normalization of real-time quantitative RT-PCR data by geometric averaging of multiple internal control genes. Genome Biol 2002, 3:1-11.
• [31]Thellin O, Elmoualij B, Heinen E, Zorzi W: A decade of improvements in quantification of gene expression and internal standard selection. Biotechnol Adv 2009, 4:323-333.
• [32]Nolan T, Hands RE, Bustin SA: Quantification of mRNA using real-time RT-PCR. Nat Protoc 2006, 1:1559-1582.
• [33]Die JV, Roman B: RNA quality assessment: a view from plant qPCR studies. J Exp Bot 2012, 63:6069-6077.
• [34]Nakatsuka A, Mizuta D, Kii Y, Myajima I, Kobayashi N: Isolation and expression analysis of flavonoid biosynthesis genes in evergreen azalea. Sci Hort 2008, 118:314-320.
• [35]Baelde HJ, Cleton-Jansen AM, Van Beerendonck H, Namba K: High quality RNA isolation from tumors with low cellularity and high extra-cellular matrix component for cDNA microarrays. Application to chondrosarcoma. J Clin Pathol 2001, 54:778-782.
• [36]Shultz DJ, Craig R, Cox-Foster DL, Mumma RO, Medford JI: RNA isolation from recalcitrant plant tissue. Plant Mol Biol Rep 1994, 12:310-316.
• [37]Mueller O, Hahnenberger K, Dittmann M, Yee H, Dubrow R, Nagle R, Ilsley D: A microfluidic system for high-speed reproducible DNA sizing and quantitation. Electrophoresis 2000, 21:128-134.
• [38]Nolan T, Hands RE, Ogunkolade W, Bustin SA: SPUD: A quantitative PCR assay for the detection of inhibitors in nucleic acid preparations. Anal Biochem 2006, 351:308-310.
• [39]Vermeulen J, De Preter K, Lefever S, Nuytens J, De Vloed F, Derveaux S, Hellemans J, Speleman F, Vandesompele J: Measurable impact of RNA quality on gene expression results from quantitative PCR. Nucl Acids Res 2011, 39:1-12.
• [40]Schroeder A, Mueller O, Stocker S, Salowsky R, Leiber M, Gassmann M, Lightfoot S, Menzel W, Granzow M, Ragg T: The RIN: and RNA integrity number for assigning integrity values to RNA measurements. BMC Mol Biol 2006, 7:3. BioMed Central Full Text
• [41]Hellemans J, Mortier G, De Paepe A, Speleman F, Vandesompele J: qBase relative quantification framework and software for management and automated analysis of real-time quantitative PCR data. Genome Biol 2007., 8 BioMed Central Full Text
• [42]De Keyser E, De Riek J, Van Bockstaele E: Discovery of species-wide EST-derived markers in Rhododendron by intron-flanking primer design. Mol Breeding 2009, 23:171-178.
• [43]Ovstebo R, Bente Foss Haug K, Lande K, Kierulf P: PCR-based calibration curves for studies of quantitative gene expression in human monocytes: development and evaluation. Clinical Biochem 2003, 49:425-432.
• [44]Wang QT, Xiao W, Mindrinos M, Davis RW: Yeast tRNA as carrier in the isolation of microscale RNA for global amplification and expression profiling. Biotechniques 2002, 33:788-796.
• [45]Quattrocchio F, Wing JF, van der Woude K, Souer E, de Vetten N, Mol J, Koes R: Molecular analysis of the anthocyanin2 gene of petunia and its role in the evolution of flower color. Plant Cell 1999, 11:1433-1444.
• [46]Streisfeld MA, Rausher MD: Altered trans-regulatory control of gene expression in multiple anthocyanin genes contributes to adaptive flower color evolution in Mimulus aurantiacus. Mol Biol Evol 2009, 26:433-444.
• [47]Bustin SA, Nolan T: Pitfalls of quantitative real-time reverse-transcription polymerase chain reaction. J Biomol Tech 2004, 15:155-166.
• [48]Fleige S, Walf V, Huch S, Prgomet C, Sehm J, Pfaffl M: Comparison of relative mRNA quantification models and the impact of RNA integrity in quantitative real-time RT-PCR. Biotechnol letters 2006, 28:1601-1613.
• [49]D’haene B, Hellemans J: The importance of quality control during qPCR data analysis. Int Drug Disc 2010, 18-24.
• [50]Imbeaud S, Graudens E, Boulanger V, Barlet X, Zaborski P, Eveno E, Mueller O, Schroeder A, Auffray C: Towards standardization of RNA quality assessment using user-independent classifiers of microcapillary electrophoresis traces. Nucl Acids Res 2005, 33:e56.
• [51]Pfaffl MW, Fleige S, Riedmaier I: Validation of lab-on-chip capillary electrophoresis systems for total RNA quality and quantity control. Biotechnol Biotechnol Equip 2008, 22:839-843.
• [52]Denisov V, Strong W, Walder M, Gringich J, Wintz H: Development and validation of RQI: an RNA quality indicator for the ExperionTM automated gel electrophoresis system. Tech Note Bio-Rad 2008., 5761
• [53]Krupp G: Stringent RNA quality control using the Agilent 2100 bioanalyzer. 2005. [Agilent Technologies application note]
• [54]Pico de Coana Y, Parody N, Fernandez-Caldas E, Alonso C: A modified protocol for RNA isolation from high polysaccharide containing Cupressus arizonica pollen. Applications for RT-PCR and phage display library construction. Mol Biotechnol 2009.
• [55]Philips MA, D’auria JC, Luck K, Gershenzon J: Evaluation of candidate reference genes for real-time quantitative PCR of plant samples using purified cDNA as template. Plant Mol Biol Rep 2009, 27:407-416.
• [56]Onate-Sanchez L, Vicente-Carbajosa J: DNA-free RNA isolation protocols for Arabidopsis thaliana, including seeds and siliques. BMC Reseach Notes 2008, 1:93. BioMed Central Full Text
• [57]De Santis C, Smith-Keune C, Jerry DR: Normalizing RT-qPCR data: are we getting the right answers? An appraisal of normalization approaches and internal reference genes from a case-study in the Finfish Lates Calcarifer. Mar Biotechnol 2011, 13:170-180.
• [58]Grunwald U, Guo W, Fischer K, Isayenkov S, Ludwig-Muller J, Hause B, Yan X, Kuster H, Franken P: Overlapping expression patterns and differential transcript levels of phosphate transporter genes in arbuscular mycorrhizal, Pi-fertilised and phytohormone treated Medicago truncatula roots. Planta 2009, 229:1023-1034.
• [59]Laurell H, Iacovoni JS, Abot A, Svec D, Maoret J-J, Arnal J-F, Kubista M: Correction of RT-qPCR data for genomic DNA-derived signals with ValidPrime. Nucl Acids Res 2012, 40:e51.
• [60]Czechowski T, Stitt M, Altmann T, Udvardi MK, Scheible WR: Genome-wide identification and testing of superior reference genes for transcript normalization in Arabidopsis. Plant Physiol 2005, 139:5-17.
• [61]Popovici V, Goldstein DR, Antonov J, Jaggi R, Delorenzi M, Wirapati P: Selecting control genes for RT-qPCR using public microarray data. BMC Bioinforma 2009., 10
• [62]Coker JS, Davies E: Selection of candidate housekeeping controls in tomato plants using EST data. Biotechniques 2003, 35:740-748.
• [63]Cruz F, Kalaoun S, Nobile P, Colombo C, Almeida J, Barros LMG, Romano E, Grossi-de-Sa MF, Vaslin M, Alves-Ferreira M: Evaluation of coffee reference genes for relative expression studies by quantitative real-time RT-PCR. Mol Breeding 2009, 23:607-616.
• [64]Klie M, Debener T: Identification of superior reference genes for data normalisation of expression studies via quantitative PCR in hybrid roses (Rosa hybrida). BMC Reserach Notes 2011, 4:518. BioMed Central Full Text
• [65]Mallona I, Lischewski S, Weiss J, Hause B, Egea-Cortines M: Validation of reference genes for quantitative real-time PCR during leaf and flower development in Petunia hybrida. BMC Plant Biol 2010., 10 BioMed Central Full Text
• [66]Regier N, Frey B: Experimental comparison of relative RT-qPCR quantification approaches for gene expression studies in poplar. BMC Mol Biol 2010, 11:57. BioMed Central Full Text
• [67]Ramakers C, Ruijter JM, Lekanne-Deprez RH, Moorman AFM: Assumption-free analysis of quantitative real-time PCR data. Neuroscience Lett 2002, 339:62-66.
• [68]Liu W, Saint DA: A new quantitative method of real time reverse transcription polymerase chain reaction assay based on simulation of polymerase chain reaction kinetics. Anal Biochem 2002, 302:52-59.
• [69]Liu W, Saint DA: Validation of a quantitative method for real time PCR kinetics. Biochem Biophys Res Comm 2002, 294:347-353.
• [70]Lalam N: Estimation of the reaction efficiency in polymerase chain reaction. J Theor Biol 2006, 242:947-953.
• [71]Rieu I, Powers SJ: Real-time quantitative RT-PCR: design, calculations and statistics. Plant Cell 2009, 21:1031-1033.
• [72]Nordgard O, Kvaloy JT, Farmen RK, Heikkila R: Error propagation in relative real-time reverse transcription polymerase chain reaction quantification models: the balance between accuracy and precision. Anal Biochem 2006, 356:182-193.
• [73]Marino JH, Cook P, Miller KS: Accurate and statistically verified quantification of relative mRNA abundances using SYBR Green I and real-time RT-PCR. J Immunol Meth 2003, 283:291-306.
• [74]Cook P, Fu C, Hickey M, Han E-S, Miller K: SAS programs for real-time RT-PCR having multiple independent samples. Bioinformatics 2004, 37:990-995.
• [75]Derveaux S, Vandesompele J, Hellemans J: How to do successful gene expression analysis using real-time PCR. Methods 2010, 50:227-230.
• [76]Kunert R, Gach JS, Vorauer-Uhl K, Engel E, Katinger H: Validated method for quantification of genetically modified organisms in samples of maize flour. J Agricul Food Chem 2006, 54:678-681.
• [77]Taverniers I, Van Bockstaele E, De Loose M: Cloned plasmid DNA fragments as calibrators for controlling GMOs: diffeent real-time duplex quantitative PCR methods. Anal Bioanal Chem 2004, 378:1198-1207.
• [78]Jansen RC, Nap JP: Genetical genomics: the added value from segregation. Trends Genet 2001, 17:388-391.
• [79]Joosen RVL, Ligterink W, Hilhorst HWM, Keurentjes JJB: Advances in genetical genomics of plants. Curr Genomics 2009, 10:540-549.
• [80]Motulsky H: Choosing an appropriate sample size. In Intuitive Biostatistics. New York: Oxford University Press; 1995:195-204.
• [81]Shi C, Uzarowska A, Ouzunova M, Landbeck M, Wenzel G, Lübberstedt T: Identification of candidate genes associated with cell wall digestibility and eQTL (expression quantitative trait loci) analysis in a Flint x Flint maize recombinant inbred line population. BMC Genomics 2007, 8:22. BioMed Central Full Text
• [82]Schwinn KE, Davies KM: Flavonoids. In Plant Pigments and their manipulation. Edited by Davies K. Oxford: Blackwell Publishing Ltd; 2004:92-149. [Annual Plant Reviews, Volume 14.]
• [83]Larsen ES, Alfenito MR, Briggs WR, Walbot V: A carnation anthocyanin mutant is complemented by the glutathione S-transferases encoded by maize Bz2 and petunia An9. Plant Cell Rep 2003, 21:900-904.
• [84]De Jong WS, Eannetta NT, De Jong DM, Bodis M: Candidate gene analysis of anthocyanin pigmentation loci in the Solanaceae. Theor Appl Genet 2004, 108:423-432.
• [85]Jung CS, Griffiths HM, De Jong DM, Cheng S, Bodis M, Kim TS, De Jong WS: The potato developer (D) locus encodes an R2R3 MYB transcription factor that regulates expression of multiple anthocyanin structural genes in tuber skin. Theor Appl Genet 2009, 120:45-57.
• [86]Kliebenstein DJ, West MA, van Leeuwen H, Loudet O: Dioerge RW and St Clair DA: Identification of QTLs controlling gene expression networks defined a priori. BMC Bioinforma 2006, 7:308. BioMed Central Full Text
• [87]De Keyser E, Shu QI, Van Bockstaele E, De Riek J: Multipoint-likelihood maximization mapping on 4 segregating populations to achieve an integrated framework map for QTL analysis in pot azalea (Rhododendron simsii hybrids). BMC Mol Biol 2010, 11:1. BioMed Central Full Text
• [88]Moore D, Dowhan D: Manipulation of DNA. Current Protocols Mol Biol 2002, 59:2.1.1-2.1.10.
• [89]Dhanasekaran S, Doherty TM, Kenneth J: Comparison of different standards for real-time PCR-based absolute quantification. J Immunol Methods 2010, 354:34-39.
• [90]Luu-The V, Paquet N, Calvo E, Cumps J: Improved real-time RT-PCR method for high-throughput measurements using second derivative calculation and double correction. Biotechniques 2005, 38:287-293.
• [91]Van Ooijen JW: MapQTL®5, software for the mapping of quantitative trait loci in experimental populations. Wageningen, The Netherlands: Kyazma BV; 2004.
• [92]Mantel N: The detection of disease clustering and a generalized regression approach. Cancer Res 1976, 27:209-220.
• [93]Liedloff AC: Mantel Nonparametric Test Calculator. Version 2.0. Australia: School of Natural Resource Sciences, Queensland University of Technology; 1999.